How big is the engineering pod?

Typically 3–6 engineers depending on scope — frontend, backend, ML, and DevOps — managed by a technical lead from our side.

Yes. All IP is yours. We hand over the full codebase with documentation.

How do you handle changes in scope?

We scope in phases so changes are natural and planned — not disruptive. We review scope at the end of each phase.

Can you work with our existing tech stack?

Yes. We assess your stack in Week 1 and build within it wherever practical. We'll flag where changes would meaningfully improve the outcome.

What happens after launch?

We offer a stabilisation period post-launch and can transition to a retainer or hand over to your team — your choice.

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Full-Stack AI Product Engineering

We operate as your engineering team — owning end-to-end delivery of production-grade AI products. Frontend, backend, infrastructure, and the AI layer. All in one pod.

FRONTEND (React)

MIDDLEWARE TIER

DATA CLUSTER

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The Problem It Solves

Building an AI product requires frontend engineers, backend engineers, ML engineers, DevOps, and product leadership — all working in sync. Most companies can't hire and coordinate all of this fast enough. We bring it as a single, accountable pod so you can move from concept to production without the coordination overhead.

Process

How It Works

Fixed scope. Clear timeline. No surprises.

Week 1

Product Scoping & Technical Discovery

We define the product scope, user flows, technical architecture, and AI integration points. We challenge assumptions early so there are no surprises in build.

Week 2–4

Foundation Build

We build the core infrastructure, data layer, and AI integration — the parts that everything else depends on.

Week 4–10

Feature Build & Iteration

We build in sprints with weekly demos. You see working software every week, not a finished product months later.

Week 10+

Production Launch & Stabilisation

We launch, monitor, and stabilise — fixing issues fast in the period right after go-live when things always surface.

What's Included

What You Get

Every engagement includes:

Full product architecture documentation

Frontend (React / Next.js or your chosen stack)

Backend APIs and data layer

AI/ML integration and model serving

Cloud infrastructure (AWS / GCP / Azure)

CI/CD pipeline and deployment automation

Security implementation and penetration test readiness

Codebase handover with documentation your team can own

Target Audience

Who It's For

Who This Is For

Founders, product leaders, and enterprise innovation teams who have a validated AI product concept and need an engineering team that can own delivery end-to-end — not just build to spec.

Who This Is NOT For

Teams looking for a cheap body-shop to execute a detailed spec. We work best with clients who want a genuine engineering partner — one that challenges decisions and takes ownership of outcomes.

Questions & Answers

Frequently Asked Questions

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